Dataset Information

Associations of Amyloid, Tau, and Neurodegeneration Biomarker Profiles With Rates of Memory Decline Among Individuals Without Dementia.

ABSTRACT:

Importance

A National Institute on Aging and Alzheimer's Association workgroup proposed a research framework for Alzheimer disease in which biomarker classification of research participants is labeled AT(N) for amyloid, tau, and neurodegeneration biomarkers.

Objective

To determine the associations between AT(N) biomarker profiles and memory decline in a population-based cohort of individuals without dementia age 60 years or older, and to determine whether biomarkers provide incremental prognostic value beyond more readily available clinical and genetic information.

Design, setting, and participants

Population-based cohort study of cognitive aging in Olmsted County, Minnesota, that included 480 nondemented Mayo Clinic Study of Aging participants who had a clinical evaluation and amyloid positron emission tomography (PET) (A), tau PET (T), and magnetic resonance imaging (MRI) cortical thickness (N) measures between April 16, 2015, and November 1, 2017, and at least 1 clinical evaluation follow-up by November 12, 2018.

Exposures

Age, sex, education, cardiovascular and metabolic conditions score, APOE genotype, and AT(N) biomarker profiles. Each of A, T, or (N) can be abnormal (+) or normal (-), resulting in 8 AT(N) profiles.

Main outcomes and measures

Primary outcome was a composite memory score measured longitudinally at 15-month intervals. Analyses measured the associations between predictor variables and the memory score, and whether AT(N) biomarker profiles significantly improved prediction of memory z score rates of change beyond a model with clinical and genetic variables only.

Results

Participants were followed up for a median of 4.8 years (interquartile range [IQR], 3.8-5.1) and 44% were women (211/480). Median (IQR) ages ranged from 67 years (65-73) in the A-T-(N)- group to 83 years (76-87) in the A+T+(N)+ group. Of the participants, 92% (441/480) were cognitively unimpaired but the A+T+(N)+ group had the largest proportion of mild cognitive impairment (30%). AT(N) biomarkers improved the prediction of memory performance over a clinical model from an R2 of 0.26 to 0.31 (P?Conclusions and relevanceAmong older persons without baseline dementia followed for a median of 4.8 years, a prediction model that included amyloid PET, tau PET, and MRI cortical thickness resulted in a small but statistically significant improvement in predicting memory decline over a model with more readily available clinical and genetic variables. The clinical importance of this difference is uncertain.

SUBMITTER: Jack CR

PROVIDER: S-EPMC6582267 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Associations of Amyloid, Tau, and Neurodegeneration Biomarker Profiles With Rates of Memory Decline Among Individuals Without Dementia.

Jack Clifford R CR Wiste Heather J HJ Therneau Terry M TM Weigand Stephen D SD Knopman David S DS Mielke Michelle M MM Lowe Val J VJ Vemuri Prashanthi P Machulda Mary M MM Schwarz Christopher G CG Gunter Jeffrey L JL Senjem Matthew L ML Graff-Radford Jonathan J Jones David T DT Roberts Rosebud O RO Rocca Walter A WA Petersen Ronald C RC

JAMA 20190601 23

<h4>Importance</h4>A National Institute on Aging and Alzheimer's Association workgroup proposed a research framework for Alzheimer disease in which biomarker classification of research participants is labeled AT(N) for amyloid, tau, and neurodegeneration biomarkers.<h4>Objective</h4>To determine the associations between AT(N) biomarker profiles and memory decline in a population-based cohort of individuals without dementia age 60 years or older, and to determine whether biomarkers provide increm ...[more]

PMID: 31211344

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Project description:Mild cognitive impairment (MCI) can be an early manifestation of Alzheimer's disease (AD) pathology, other pathologic entities [e.g., cerebrovascular disease, Lewy body disease, LATE (limbic-predominant age-related TDP-43 encephalopathy)], or mixed pathologies, with concomitant AD- and non-AD pathology being particularly common, albeit difficult to identify, in living MCI patients. The National Institute on Aging and Alzheimer's Association (NIA-AA) A/T/(N) [β-Amyloid/Tau/(Neurodegeneration)] AD research framework, which classifies research participants according to three binary biomarkers [β-amyloid (A+/A-), tau (T+/T-), and neurodegeneration (N+/N-)], provides an indirect means of identifying such cases. Individuals with A+T-(N+) MCI are thought to have both AD pathologic change, given the presence of β-amyloid, and non-AD pathophysiology, given neurodegeneration without tau, because in typical AD it is tau accumulation that is most tightly linked to neuronal injury and cognitive decline. Thus, in A+T-(N+) MCI (hereafter referred to as "mismatch MCI" for the tau-neurodegeneration mismatch), non-AD pathology is hypothesized to drive neurodegeneration and symptoms, because β-amyloid, in the absence of tau, likely reflects a preclinical stage of AD. We compared a group of individuals with mismatch MCI to groups with A+T+(N+) MCI (or "prodromal AD") and A-T-(N+) MCI (or "neurodegeneration-only MCI") on cross-sectional and longitudinal cognition and neuroimaging characteristics. β-amyloid and tau status were determined by CSF assays, while neurodegeneration status was based on hippocampal volume on MRI. Overall, mismatch MCI was less "AD-like" than prodromal AD and generally, with some exceptions, more closely resembled the neurodegeneration-only group. At baseline, mismatch MCI had less episodic memory loss compared to prodromal AD. Longitudinally, mismatch MCI declined more slowly than prodromal AD across all included cognitive domains, while mismatch MCI and neurodegeneration-only MCI declined at comparable rates. Prodromal AD had smaller baseline posterior hippocampal volume than mismatch MCI, and whole brain analyses demonstrated cortical thinning that was widespread in prodromal AD but largely restricted to the medial temporal lobes (MTLs) for the mismatch and neurodegeneration-only MCI groups. Longitudinally, mismatch MCI had slower rates of volume loss than prodromal AD throughout the MTLs. Differences in cross-sectional and longitudinal cognitive and neuroimaging measures between mismatch MCI and prodromal AD may reflect disparate underlying pathologic processes, with the mismatch group potentially being driven by non-AD pathologies on a background of largely preclinical AD. These findings suggest that β-amyloid status alone in MCI may not reveal the underlying driver of symptoms with important implications for enrollment in clinical trials and prognosis.

Project description:In a 2014 cross-sectional analysis, we showed that amyloid and neurodegeneration biomarker states in participants with no clinical impairment varied greatly with age, suggesting dynamic within-person processes. In this longitudinal study, we aimed to estimate rates of transition from a less to a more abnormal biomarker state by age in individuals without dementia, as well as to assess rates of transition to dementia from an abnormal state.Participants from the Mayo Clinic Study of Aging (Olmsted County, MN, USA) without dementia at baseline were included in this study, a subset of whom agreed to multimodality imaging. Amyloid PET (with (11)C-Pittsburgh compound B) was used to classify individuals as amyloid positive (A(+)) or negative (A(-)). (18)F-fluorodeoxyglucose ((18)F-FDG)-PET and MRI were used to classify individuals as neurodegeneration positive (N(+)) or negative (N(-)). We used all observations, including those from participants who did not have imaging results, to construct a multistate Markov model to estimate four different age-specific biomarker state transition rates: A(-)N(-) to A(+)N(-); A(-)N(-) to A(-)N(+) (suspected non-Alzheimer's pathology); A(+)N(-) to A(+)N(+); and A(-)N(+) to A(+)N(+). We also estimated two age-specific rates to dementia: A(+)N(+) to dementia and A(-)N(+) to dementia. Using these state-to-state transition rates, we estimated biomarker state frequencies by age.At baseline (between Nov 29, 2004, to March 7, 2015), 4049 participants did not have dementia (3512 [87%] were clinically normal and 537 [13%] had mild cognitive impairment). 1541 individuals underwent imaging between March 28, 2006, to April 30, 2015. Transition rates were low at age 50 years and, with one exception, exponentially increased with age. At age 85 years compared with age 65 years, the rate was nearly 11-times higher (17.2 vs 1.6 per 100 person-years) for the transition from A(-)N(-) to A(-)N(+), three-times higher (20.8 vs 6.1) for A(+)N(-) to A(+)N(+), and five-times higher (13.2 vs 2.6) for A(-)N(+) to A(+)N(+). The rate of transition was also increased at age 85 years compared with age 65 years for A(+)N(+) to dementia (7.0 vs 0.8) and for A(-)N(+) to dementia (1.7 vs 0.6). The one exception to an exponential increase with age was the transition rate from A(-)N(-) to A(+)N(-), which increased from 4.0 transitions per 100 person-years at age 65 years to 6.9 transitions per 100 person-years at age 75 and then plateaued beyond that age. Estimated biomarker frequencies by age from the multistate model were similar to cross-sectional biomarker frequencies.Our transition rates suggest that brain ageing is a nearly inevitable acceleration toward worse biomarker and clinical states. The one exception is the transition to amyloidosis without neurodegeneration, which is most dynamic from age 60 years to 70 years and then plateaus beyond that age. We found that simple transition rates can explain complex, highly interdependent biomarker state frequencies in our population.National Institute on Aging, Alexander Family Professorship of Alzheimer's Disease Research, the GHR Foundation.

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Project description:ImportanceAssessing the ability of Alzheimer disease neuroimaging markers to predict short-term cognitive decline among clinically normal (CN) individuals is critical for upcoming secondary prevention trials using cognitive outcomes.ObjectiveTo determine whether neuroimaging markers of β-amyloid (Aβ) and neurodegeneration (ND) are independently or synergistically associated with longitudinal cognitive decline in CN individuals.Design, setting, and participantsAcademic medical center longitudinal natural history study among 166 CN individuals (median age, 74 years; 92 women).Main outcomes and measuresThe Aβ status was determined with Pittsburgh Compound B-positron emission tomography, while ND was assessed using 2 a priori measures, hippocampus volume (magnetic resonance imaging) and glucose metabolism (positron emission tomography with fludeoxyglucose F 18), extracted from Alzheimer disease-vulnerable regions. Based on imaging markers, CN individuals were categorized into the following preclinical Alzheimer disease stages: stage 0 (Aβ-/ND-), stage 1 (Aβ(+)/ND-), stage 2 (Aβ(+)/ND(+)), and suspected non-Alzheimer disease pathology (Aβ-/ND(+)). Cognition was assessed with a composite of neuropsychological tests administered annually.ResultsThe Aβ(+) CN individuals were more likely to be classified as ND+: 59.6% of Aβ(+) CN individuals were ND(+), whereas 31.9% of Aβ- CN individuals were ND(+) (odds ratio, 3.14; 95% CI, 1.44-7.02; P = .004). In assessing longitudinal cognitive performance, practice effects were evident in CN individuals negative for both Aβ and ND, whereas diminished practice effects were observed in CN individuals positive for either Aβ or ND. Decline over time was observed only in CN individuals positive for both Aβ and ND, and decline in this group was significantly greater than that in all other groups (P < .001 for all). A significant interaction term between Aβ and ND confirmed that this decline was greater than the additive contributions of Aβ and ND (P = .04).Conclusions and relevanceThe co-occurrence of Aβ and ND accelerates cognitive decline in CN individuals. Therefore, both factors are important to consider in upcoming secondary prevention trials targeting CN individuals at high risk for progression to the symptomatic stages of Alzheimer disease.

Dataset Information

Associations of Amyloid, Tau, and Neurodegeneration Biomarker Profiles With Rates of Memory Decline Among Individuals Without Dementia.

Importance

Objective

Design, setting, and participants

Exposures

Main outcomes and measures

Results

Publications

Associations of Amyloid, Tau, and Neurodegeneration Biomarker Profiles With Rates of Memory Decline Among Individuals Without Dementia.

Similar Datasets

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